Solution Seeker speaking at the SPE Intelligent Energy Conference
In our paper to SPE IE 2016, we present a completely data-driven approach to production optimization that exposes uncertainty and supports informed decisions. We hope to spark a discussion about the uncertainty shrouding many operational decisions.
- Author
- Solution Seeker
- Publish date
- · 1 min read
Oil production engineers are daily faced with vast amounts of real-time sensory data, which is processed to extract important information about the state of the production system. Data processing and analysis is done by the human brain, with support from machines. Traditionally, valuable information about the uncertainty in the data is discarded during processing. This leads to estimates without uncertainty measures, which in some cases become meaningless.
«Furthermore, whenever humans are involved, data processing will be influenced by cognitive biases—such as the confirmation bias, in which the engineer favors answers that confirm presumptions. Most production engineers have not been trained to handle uncertainty with proper statistical tools and may not be aware of his or hers cognitive biases. As a result, suboptimal decisions are made with a negative effect on the performance of the asset.»
Our paper and corresponding presentation is a part of the technical session named "Real Time Production Optimisation". We will present a data-driven approach to production estimation and optimization that carries uncertainty information all the way through the data pipeline. This ultimately results in better decision making and increased production.
